Introduce instrumentation for tool calling using the Micrometer Observation API.
By default, metadata about tool calling are exported as metrics and traces.
Optionally, the actual tool call input and result can be exported as well by enabling the dedicated feature flag.
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
This removes the possible large amount of data that was attached
to spans and it logs the data out. This change also removes the direct
dependency on the OTel SDK. approach for content in Spring AI.
Refactors the observability approach for content in Spring AI:
- Replace content observation filters with logging handlers
- Rename configuration properties to better reflect their purpose:
- `include-prompt` → `log-prompt`
- `include-completion` → `log-completion`
- `include-query-response` → `log-query-response`
- Add TracingAwareLoggingObservationHandler for trace-aware logging
- Replace micrometer-tracing-bridge-otel with micrometer-tracing
- Remove event-based tracing in favor of direct logging
- Update documentation to reflect these changes (add breaking-changes section)
- Rename includePrompt to logPrompt in observation properties. Updated in ChatClientBuilderProperties, ChatObservationProperties, and ImageObservationProperties.
Signed-off-by: Christian Tzolov <christian.tzolov@broadcom.com>
- Remove deprecated constructor method Media(MimeType mimeType, URL url) from Media
- Remove deprecated builder method data(URL url) from Media builder
- Update references to use the builder and the data(URI) methods
Signed-off-by: Ilayaperumal Gopinathan <ilayaperumal.gopinathan@broadcom.com>
- Move evaluation core classes (Request, Response, Evaluator) to spring-ai-commons.
- Move chat-specific evaluators (FactChecking, Relevancy) to spring-ai-client-chat#evaluation package.
- Move OutputConverter implementations and related classes to spring-ai-model#converter package.
- Move MetadataEnricher transformer classes to spring-ai-model#transformer package.
- Move PromptAssert utility to spring-ai-rag#util package.
- Update relevant pom.xml files and adjust imports in affected classes.
- Document class movements in upgrade-notes.adoc for M8 release.
This refactoring improves module organization and separation of concerns.
Signed-off-by: Mark Pollack <mark.pollack@broadcom.com>
Introduce defining Media objects from a URI, deprecating the previous URL support.
Fixes gh-1147
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
- Introduce new TemplateRenderer API providing the logic for rendering an input template.
- Update the PromptTemplate API to accept a TemplateRenderer object at construction time.
- Move ST logic to StTemplateRenderer implementation, used by default in PromptTemplate. Additionally, make start and end delimiter character configurable.
Relates to gh-2655
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
- Avoid overlapping package names
Changed in spring-ai-commons package from org.sf.ai.model to org.sf.ai.content
Refactor advisor module name to be spring-ai-advisors-vector-store
Moved advisors into org.springframework.ai.chat.client.advisor.vectorstore
- Created top level memory directory
- Create new module spring-ai-model-chat-memory-neo4j and moved neo4j memory classes out of the vectorstore module
Updated neo4j autoconfiguation
Extract functionality from spring-ai-core into dedicated modules:
- spring-ai-commons: Common utilities and document handling
- spring-ai-model: Core model interfaces and implementations
- spring-ai-vector-store: Vector store abstraction and implementation
This modularization creates clearer responsibility boundaries and allows
consumers to include only what they need. The restructuring will make the
codebase easier to maintain and extend as the project grows.
